Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I /

The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed a...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Appice, Annalisa (Επιμελητής έκδοσης), Rodrigues, Pedro Pereira (Επιμελητής έκδοσης), Santos Costa, Vítor (Επιμελητής έκδοσης), Soares, Carlos (Επιμελητής έκδοσης), Gama, João (Επιμελητής έκδοσης), Jorge, Alípio (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2015.
Έκδοση:1st ed. 2015.
Σειρά:Lecture Notes in Computer Science, 9284
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Περιγραφή
Περίληψη:The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, and 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.
Φυσική περιγραφή:LVIII, 709 p. 160 illus. online resource.
ISBN:9783319235288
ISSN:0302-9743 ;